Spectroscopic analysis makes use of a change in the properties of energy, such as light, after it interacts with a material sample. For example, the property of light most often correlated to a property of the sample is the intensity of the light. According to the Beer-Lambert law, the intensity of light transmitted through a fluid sample varies exponentially with respect to the absorptivity of the sample (usually expressed as molar absorptivity or molecular absorptivity), the path length through which the light is transmitted, and the concentration of the absorbing species in the sample.
Spectroscopic analysis of formation fluid can be performed downhole using a downhole tool to estimate the fluid's compositional concentrations as well as other fluid properties. The analysis of fluid compositional concentrations can be at least self-consistent.
Methods for optical fluid identification can apply diverse predictive models to evaluate different fluid properties of interest. Each model is typically calibrated on selected fluid samples from a standard fluid library under stabilized conditions using a number of predetermined parameters as model inputs that may have been derived from, or simulated with, particular detector outputs of an optical sensor. Data prediction using standard calibration inputs is usually accurate on training samples utilized for model development. However, problems in predicting formation fluid composition can arise due to field data being out of calibration data range, optical signal intensity variation with severe environment and tool conditioning, and one or more optical elements that fail to operate properly.